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Design the architecture for an object detection system.


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The architecture for an object detection system consists of two main components: a feature extractor and a predictor. The feature extractor is responsible for extracting the features of an image, such as color, intensity, location, shape, etc. The feature extractor can be a CNN (Convolutional Neural Network), which extracts the features from the image and passes them to the predictors. The predictor then uses a classifier, such as a Support Vector Machine, to identify the object from the features. The classifier then gives an output which can be used to identify the object in the image. The architecture also includes data augmentation and optimization for improved performance.